Citation: | TU X Y,SHAO S G,ZHANG X T,et al.Analysis of transmission spatio-temporal pattern of atmospheric heavy pollution events based on spatiotemporal data mining[J].Journal of Environmental Engineering Technology,2023,13(3):940-948 doi: 10.12153/j.issn.1674-991X.20220696 |
In order to explore the spatiotemporal pattern of regional air pollution transmission and diffusion and to support the regional joint prevention and emergency control of atmospheric environment pollution, a new spatiotemporal data mining approach was proposed based on air-quality ground observation data. The algorithms were built to identify the regional transmission paths and intensity of heavily polluted air masses. The case study on PM2.5 heavy pollution events in Beijing-Tianjin-Hebei region during January-March and October-December, 2021 was conducted to verify the algorithms. The results showed that there were 17 regional heavy pollution events during this period in Beijing-Tianjin-Hebei region. There were 3, 7, and 7 long (>48 h), medium-long (24-48 h), and short (<24 h) pollution events, respectively. All long pollution events occurred in spring. Their pollution intensity was the highest among the three event types, and the polluted area and pollution transmission area covered the entire study area. The medium-long and short pollution events occurred in spring and winter. Their pollution intensity was lower than that of long events. Medium-long events' polluted area coverage (>80%) was higher than that of short events (<63%). There were seasonal differences in the area covered by pollution transmission for medium-long pollution events. In terms of the transportation intensity coefficient of heavy pollution transmission in Beijing-Tianjin-Hebei region generally conformed to the law that local pollution intensity coefficient (0.32-1.00) was the highest, followed by intra-city pollution transmission (0.01-0.95), and inter-city pollution (0.00-0.28). Among them, the inter-city transmission intensity of Xingtai was greater than its intra-city transmission, and the impact of Hengshui on surrounding cities was lower than the average level.
[1] |
燕丽, 雷宇, 张伟.我国区域大气污染防治协作历程与展望[J]. 中国环境管理,2021,13(5):61-68. doi: 10.16868/j.cnki.1674-6252.2021.05.061
YAN L, LEI Y, ZHANG W. Progress and prospect of regional air pollution prevention and control cooperation in China[J]. Chinese Journal of Environmental Management,2021,13(5):61-68. doi: 10.16868/j.cnki.1674-6252.2021.05.061
|
[2] |
徐绪堪, 刘思琪, 张宏阳.城市群视角下大气污染空间效应和影响因素研究[J]. 科技管理研究,2020,40(15):244-251. doi: 10.3969/j.issn.1000-7695.2020.15.035
XU X K, LIU S Q, ZHANG H Y. Study of spatial effects and influencing factors of air pollution from perspective of urban agglomeration[J]. Science and Technology Management Research,2020,40(15):244-251. doi: 10.3969/j.issn.1000-7695.2020.15.035
|
[3] |
HE Z J, DENG M, CAI J N, et al. Mining spatiotemporal association patterns from complex geographic phenomena[J]. International Journal of Geographical Information Science,2020,34(6):1162-1187. doi: 10.1080/13658816.2019.1566549
|
[4] |
薛俭, 陈强强.京津冀大气污染联防联控区域细分与等级评价[J]. 环境污染与防治,2020,42(10):1305-1309. doi: 10.15985/j.cnki.1001-3865.2020.10.023
XUE J, CHEN Q Q. Range and gradation evaluation of air pollution joint prevention and control in Bejing-Tianjin-Hebei region, China[J]. Environmental Pollution & Control,2020,42(10):1305-1309. doi: 10.15985/j.cnki.1001-3865.2020.10.023
|
[5] |
GAO J J, WANG K, WANG Y, et al. Temporal-spatial characteristics and source apportionment of PM2.5 as well as its associated chemical species in the Beijing-Tianjin-Hebei region of China[J]. Environmental Pollution,2018,233:714-724. doi: 10.1016/j.envpol.2017.10.123
|
[6] |
王燕丽, 薛文博, 雷宇, 等.京津冀区域PM2.5污染相互输送特征[J]. 环境科学,2017,38(12):4897-4904.
WANG Y L, XUE W B, LEI Y, et al. Regional transport matrix study of PM2.5 in Jingjinji Region, 2015[J]. Environmental Science,2017,38(12):4897-4904.
|
[7] |
殷丽娜, 褚旸晰, 段菁春, 等.“2+26”城市一次多因素叠加重污染过程的特征分析[J]. 环境科学研究,2019,32(12):2022-2030. doi: 10.13198/j.issn.1001-6929.2019.07.19
YIN L N, CHU Y X, DUAN J C, et al. Characteristics of a multi-factor superimposing haze episode in ‘2+26' cities[J]. Research of Environmental Sciences,2019,32(12):2022-2030. doi: 10.13198/j.issn.1001-6929.2019.07.19
|
[8] |
沈洪艳, 吕宗璞, 师华定, 等.基于HYSPLIT模型的京津冀地区大气污染物输送的路径分析[J]. 环境工程技术学报,2018,8(4):359-366.
SHEN H Y, LÜ Z P, SHI H D, et al. Route analysis of air pollutant transport in Beijing-Tianjin-Hebei region based on HYSPLIT model[J]. Journal of Environmental Engineering Technology,2018,8(4):359-366.
|
[9] |
崔宏, 刘肖, 秦巧燕.汾渭平原典型污染城市PM2.5来源分布及 传输分析[J]. 环境工程技术学报,2022,12(5):1593-1600.
CUI H, LIU X, QIN Q Y. PM2.5 source distribution and transmission in the typical city of the Fenwei Plain[J]. Journal of Environmental Engineering Technology,2022,12(5):1593-1600.
|
[10] |
王媛, 李玥, 乔治, 等.京津冀城市群大气污染传输规律研究: 两组排放清单的比较分析[J]. 中国环境科学,2019,39(11):4561-4569. doi: 10.3969/j.issn.1000-6923.2019.11.010
WANG Y, LI Y, QIAO Z, et al. Atmospheric transmission rule on air pollution in Beijing-Tianjin-Hebei urban agglomeration: a comparative analysis of two emission inventories[J]. China Environmental Science,2019,39(11):4561-4569. doi: 10.3969/j.issn.1000-6923.2019.11.010
|
[11] |
安海岗, 张翠芝, 赵素彦.复杂网络视域下京津冀及周边城市空气质量空间关联、季节演化与协同治理[J]. 河北地质大学学报,2021,44(5):112-118.
AN H G, ZHANG C Z, ZHAO S Y. Spatial correlation, seasonal evolution and collaborative governance of air quality in Beijing-Tianjin-Hebei and its surrounding cities from the perspective of complex network[J]. Journal of Hebei GEO University,2021,44(5):112-118.
|
[12] |
SUGIHARA G, MAY R, YE H, et al. Detecting causality in complex ecosystems[J]. Science,2012,338:496-500. doi: 10.1126/science.1227079
|
[13] |
CHEN Z Y, ZHUANG Y, XIE X M, et al. Understanding long-term variations of meteorological influences on ground ozone concentrations in Beijing During 2006-2016[J]. Environmental Pollution,2019,245:29-37. doi: 10.1016/j.envpol.2018.10.117
|
[14] |
梅梅, 徐大海, 朱蓉, 等.减排措施与气象因子对2013—2019年中国大陆地区PM2.5浓度变化的贡献[J]. 环境科学学报,2021,41(7):2519-2529.
MEI M, XU D H, ZHU R, et al. Contributions of emission reduction measures and meteorological factors to the changes in PM2.5 concentration over China's mainland from 2013 to 2019[J]. Acta Scientiae Circumstantiae,2021,41(7):2519-2529.
|
[15] |
姚森, 张晗宇, 王晓琦, 等.2016年1月京津冀地区大气污染特征与多尺度传输量化评估[J]. 环境科学,2021,42(2):534-545. doi: 10.13227/j.hjkx.202006042
YAO S, ZHANG H Y, WANG X Q, et al. Air pollution characteristics and quantitative evaluation of multi-scale transport in the Beijing-Tianjin-Hebei region in January, 2016[J]. Environmental Science,2021,42(2):534-545. doi: 10.13227/j.hjkx.202006042
|
[16] |
WANG X Q, WEI W, CHENG S Y, et al. Characteristics and classification of PM2.5 pollution episodes in Beijing from 2013 to 2015[J]. Science of the Total Environment,2018,612:170-179. doi: 10.1016/j.scitotenv.2017.08.206
|
[17] |
ZHANG H Y, CHENG S Y, WANG X Q, et al. Continuous monitoring, compositions analysis and the implication of regional transport for submicron and fine aerosols in Beijing, China[J]. Atmospheric Environment,2018,195:30-45. doi: 10.1016/j.atmosenv.2018.09.043
|
[18] |
CHEN D S, LIU X X, LANG J L, et al. Estimating the contribution of regional transport to PM2.5 air pollution in a rural area on the North China Plain[J]. Science of the Total Environment,2017,583:280-291. doi: 10.1016/j.scitotenv.2017.01.066
|
[19] |
ZHANG S, ZHOU Z M, YE C L, et al. Analysis of a pollution transmission process in Hefei City based on mobile lidar[J]. EPJ Web of Conferences,2020,237:02006. doi: 10.1051/epjconf/202023702006
|
[20] |
杨红, 谢海燕, 鲍昱璇, 等.阿克苏市春季PM10和PM2.5输送路径及潜在源分析[J]. 四川环境,2022,41(3):71-78.
YANG H, XIE H Y, BAO Y X, et al. Analysis of transmission paths and potential sources of PM10 and PM2.5 in Aksu in spring[J]. Sichuan Environment,2022,41(3):71-78.
|
[21] |
DU M, LIU W, HAO Y. Spatial correlation of air pollution and its causes in northeast China[J]. International Journal of Environmental Research and Public Health,2021,18(20):10619. doi: 10.3390/ijerph182010619
|
[22] |
SONG C, HUANG G Y, ZHANG B, et al. Modeling air pollution transmission behavior as complex network and mining key monitoring station[J]. IEEE Access, 2019, 7: 121245-121254.
|
[23] |
MORAN P A P. The interpretation of statistical maps[J]. Journal of the Royal Statistical Society:Series B (Methodological),1948,10(2):243-251. doi: 10.1111/j.2517-6161.1948.tb00012.x
|
[24] |
刘丹, 花家嘉, 杨雨灵, 等.京津冀地区本地源污染贡献分型研究[J]. 中国资源综合利用,2022,40(6):7-12. doi: 10.3969/j.issn.1008-9500.2022.06.003
LIU D, HUA J J, YANG Y L, et al. Research on contribution classification of local source pollution in Beijing-Tianjin-Hebei region[J]. China Resources Comprehensive Utilization,2022,40(6):7-12. □ doi: 10.3969/j.issn.1008-9500.2022.06.003
|